Robot Learning Engineer
Impact: Physical automation and human augmentation through intelligent robotic systems
Develop machine learning systems that enable robots to learn from demonstrations, simulation, and real-world interaction. Design imitation learning, reinforcement learning, and sim-to-real transfer pipelines for physical robot manipulation and navigation.
What the day looks like
- People interaction
- Moderate
- Team vs solo
- 55% Team / 45% Solo
- Client facing
- Rarely
- Impact visibility
- High
- Travel
- 10 to 20% for lab visits and robot deployment sites
- Schedule flexibility
- Moderate
- Remote work
- Hybrid
- Typical work hours
- 45 to 55 hours/week
- Stress level
- High
At a glance
- Median salary
- $170,000
- Entry-level
- $120,000 - $150,000
- Senior
- $225,000+
- Growth by 2033
- 30% (much faster than average)
- Demand
- Growing Fast
- Freelance potential
- Very Low
- Salary growth potential
- High - 65 to 85% growth from entry to senior
- Typical student debt
- $30,000 - $80,000
Skills you'll use
Hard skills
- PyTorch
- ROS2
- Isaac Sim
- Python
- Reinforcement learning
- Imitation learning
- C++
Soft skills
- Problem-solving
- Intellectual curiosity
- Systems thinking
- Persistence
- Collaboration
Technical complexity: Very High
How to get there
- Minimum education
- Master's Degree
- Licensing
- No
- Years to mid-career
- 3 to 5 years
- Years to senior
- 7 to 10 years
- Career switching
- Very Hard
Where this career leads
How people arrive here
Where you can go from here
Typical progression
- ML Engineer > Robot Learning Engineer > Senior Robot Learning Engineer > Staff Robotics ML Engineer > Principal Scientist
Future outlook
- Automation probability
- 5% extremely low risk as the role is building the next generation of physical automation
- AI disruption risk
- Low
- Demand trend
- Growing Fast
How people feel about it
- Overall satisfaction
- 8.5/10
- Meaning
- 9/10
- Work-life balance
- 6.5/10
- Prestige
- 8.4/10
- Social perception
- Very High